Impact Analysis of a Pharmacist-Led Home-Medication Review Service Within an Interprofessional Outreach Team
Bibliographic record
Abstract
OBJECTIVE: To describe the demographic and clinical characteristics of frail and homebound communitydwelling older patients receiving a home medication review (HMR) conducted by a home-visiting pharmacist; the types of drug therapy problems (DTPs) that were identified; the types of clinical interventions being recommended and their implementation rate. DESIGN: Retrospective, cross-sectional chart-review study using data from patient records. SETTING: Homes of patients receiving a HMR by a community pharmacy-based consulting home-visiting pharmacist. PATIENTS: 171 patients received a HMR between January 1, 2016, and May 31, 2018. INTERVENTION: Patients received a comprehensive HMR by a home-visiting pharmacist working as a member of an interprofessional geriatrics team. MAIN OUTCOME MEASURES: Charlson Comorbidity Index (CCI) score, comorbidities, use of potentially inappropriate medications, DTPs identified, number and type of clinical interventions being recommended and successfully implemented. RESULTS: Patients had a mean age of 81 years (range: 54-100 years), majority were 65 years of age or older (95%), and female (59%). Fifty-three percent of patients had a CCI score of 1 to 2, and 93.6% were experiencing multi-morbidity and polypharmacy. Patients used an average of 13.0 medications, and 76.1% were found to be using at least 1 potentially inappropriate medication. In total, the home-visiting pharmacist identified 827 DTPs and made 1088 recommendations with a successful implementation rate of 74%. CONCLUSIONS: Frail and homebound communitydwelling older adults referred for a HMR were observed to be using a high number of medications with a significant number of DTPs identified. Offering HMRs was an effective method for a community-based pharmacist to make acceptable recommendations to optimize medication therapy management for frail older patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".